| Time-LLM: Time Series Forecasting by Reprogramming Large Language Models M Jin, S Wang, L Ma, Z Chu, JY Zhang, X Shi, PY Chen, Y Liang, YF Li, ... International Conference on Learning Representations (ICLR), 2024 | 1275 | 2024 |
| Graph Self-Supervised Learning: A Survey Y Liu, M Jin, S Pan, C Zhou, Y Zheng, F Xia, SY Philip IEEE Transactions on Knowledge and Data Engineering 35 (6), 5879-5900, 2022 | 853 | 2022 |
| A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection M Jin, HY Koh, Q Wen, D Zambon, C Alippi, GI Webb, I King, S Pan IEEE Transactions on Pattern Analysis and Machine Intelligence 46, 10466-10485, 2024 | 558 | 2024 |
| Foundation Models for Time Series Analysis: A Tutorial and Survey Y Liang, H Wen, Y Nie, Y Jiang, M Jin, D Song, S Pan, Q Wen Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and …, 2024 | 402 | 2024 |
| Self-Supervised Learning for Time Series Analysis: Taxonomy, Progress, and Prospects K Zhang, Q Wen, C Zhang, R Cai, M Jin, Y Liu, JY Zhang, Y Liang, ... IEEE Transactions on Pattern Analysis and Machine Intelligence 46, 6775-6794, 2024 | 330 | 2024 |
| Generative and Contrastive Self-Supervised Learning for Graph Anomaly Detection Y Zheng, M Jin, Y Liu, L Chi, KT Phan, YPP Chen IEEE Transactions on Knowledge and Data Engineering 35 (12), 12220-12233, 2021 | 237 | 2021 |
| Large Models for Time Series and Spatio-Temporal Data: A Survey and Outlook M Jin, Q Wen, Y Liang, C Zhang, S Xue, X Wang, J Zhang, Y Wang, ... arXiv preprint arXiv:2310.10196, 2023 | 224 | 2023 |
| Multivariate Time Series Forecasting with Dynamic Graph Neural ODEs M Jin, Y Zheng, YF Li, S Chen, B Yang, S Pan IEEE Transactions on Knowledge and Data Engineering 35 (9), 9168-9180, 2022 | 222 | 2022 |
| Multi-Scale Contrastive Siamese Networks for Self-Supervised Graph Representation Learning M Jin, Y Zheng, YF Li, C Gong, C Zhou, S Pan International Joint Conference on Artificial Intelligence (IJCAI), 2021 | 210 | 2021 |
| ANEMONE: Graph Anomaly Detection with Multi-Scale Contrastive Learning M Jin, Y Liu, Y Zheng, L Chi, YF Li, S Pan Proceedings of the 30th ACM International Conference on Information …, 2021 | 203 | 2021 |
| Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Experts X Shi, S Wang, Y Nie, D Li, Z Ye, Q Wen, M Jin International Conference on Learning Representations (ICLR, Spotlight), 2025 | 196 | 2025 |
| What Can Large Language Models Tell Us about Time Series Analysis M Jin, Y Zhang, W Chen, K Zhang, Y Liang, B Yang, J Wang, S Pan, ... International Conference on Machine Learning (ICML), 2024 | 169* | 2024 |
| Neural Temporal Walks: Motif-Aware Representation Learning on Continuous-Time Dynamic Graphs M Jin, YF Li, S Pan Advances in Neural Information Processing Systems (NeurIPS), 2022 | 132 | 2022 |
| A Survey on Diffusion Models for Time Series and Spatio-Temporal Data Y Yang, M Jin, H Wen, C Zhang, Y Liang, L Ma, Y Wang, C Liu, B Yang, ... ACM Computing Surveys, 2024 | 127 | 2024 |
| Correlation-aware Spatial-Temporal Graph Learning for Multivariate Time-series Anomaly Detection Y Zheng, HY Koh, M Jin, L Chi, KT Phan, S Pan, YPP Chen, W Xiang IEEE Transactions on Neural Networks and Learning Systems 35 (9), 11802-11816, 2023 | 88 | 2023 |
| TimeMixer++: A General Time Series Pattern Machine for Universal Predictive Analysis S Wang, J Li, X Shi, Z Ye, B Mo, W Lin, S Ju, Z Chu, M Jin International Conference on Learning Representations (ICLR, Oral), 2025 | 85 | 2025 |
| Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting S Zhong, W Ruan, M Jin, H Li, Q Wen, Y Liang International Conference on Machine Learning (ICML), 2025 | 46 | 2025 |
| Towards Graph Self-Supervised Learning with Contrastive Adjusted Zooming Y Zheng, M Jin, S Pan, YF Li, H Peng, M Li, Z Li IEEE Transactions on Neural Networks and Learning Systems 35 (7), 8882-8896, 2022 | 35 | 2022 |
| Time-MQA: Time Series Multi-Task Question Answering with Context Enhancement Y Kong, Y Yang, Y Hwang, W Du, S Zohren, Z Wang, M Jin, Q Wen Proceedings of the 63rd Annual Meeting of the Association for Computational …, 2025 | 34 | 2025 |
| Graph Spatiotemporal Process for Multivariate Time Series Anomaly Detection with Missing Values Y Zheng, HY Koh, M Jin, L Chi, H Wang, KT Phan, YPP Chen, S Pan, ... Information Fusion 106, 102255, 2024 | 34 | 2024 |
Shirui PanProfessor, ARC Future Fellow, FQA, Director of TrustAGI Lab, Griffith UniversityVerified email at griffith.edu.au
